WAIS Seminar:Let's SoFWIReD!

Title: Let’s SoFWIReD! Time: Wed, 21 May 2014 11:00-11:50 Location: Building 32, Room 3077 Speaker: Dr Sepi Chakaveh Abstract The information age as we know it has its roots in several enabling technologies – most of all the World Wide Web – for the provision of truly global connectivity. The emergence of a Web of Big Data in terms of the publication and analysis of Open Data provides new insights about the impact of the Web in our society. The second most important technology in this regard has been the emergence of streaming processes based on new and innovative compression methods such as MP3 so that audio and video content becomes accessible to everyone on the Web. The SoFWIReD team is developing comprehensive, interoperable platforms for data and knowledge driven processing of Open Data and will investigate aspects of collective intelligence. Insights generated in the project will form the basis for supporting companies through consulting, organisational development, and software solutions so that they can master the collective intelligence transition. The seminar will present how the project addresses the research topics of web observatory, dynamic media objects, crowd-sourced open data and Internet services. At the end of a talk a number of demos will be shown in the context of SoFWIReD’s Dynamic Media Object.

COMP1205 Legal Perspectives: Information, Data and Living in a Connected World

List of topics and Slides which summarise legal perspectives with suggested methods on how to revise for the exam

Data-Driven Text Generation using Neural Networks & Provenance is Complicated and Boring — Is there a solution?

Title: Data-Driven Text Generation using Neural Networks Speaker: Pavlos Vougiouklis, University of Southampton Abstract: Recent work on neural networks shows their great potential at tackling a wide variety of Natural Language Processing (NLP) tasks. This talk will focus on the Natural Language Generation (NLG) problem and, more specifically, on the extend to which neural network language models could be employed for context-sensitive and data-driven text generation. In addition, a neural network architecture for response generation in social media along with the training methods that enable it to capture contextual information and effectively participate in public conversations will be discussed. Speaker Bio: Pavlos Vougiouklis obtained his 5-year Diploma in Electrical and Computer Engineering from the Aristotle University of Thessaloniki in 2013. He was awarded an MSc degree in Software Engineering from the University of Southampton in 2014. In 2015, he joined the Web and Internet Science (WAIS) research group of the University of Southampton and he is currently working towards the acquisition of his PhD degree in the field of Neural Network Approaches for Natural Language Processing. Title: Provenance is Complicated and Boring — Is there a solution? Speaker: Darren Richardson, University of Southampton Abstract: Paper trails, auditing, and accountability — arguably not the sexiest terms in computer science. But then you discover that you've possibly been eating horse-meat, and the importance of provenance becomes almost palpable. Having accepted that we should be creating provenance-enabled systems, the challenge of then communicating that provenance to casual users is not trivial: users should not have to have a detailed working knowledge of your system, and they certainly shouldn't be expected to understand the data model. So how, then, do you give users an insight into the provenance, without having to build a bespoke system for each and every different provenance installation? Speaker Bio: Darren is a final year Computer Science PhD student. He completed his undergraduate degree in Electronic Engineering at Southampton in 2012.